Triple

T25434355
Position Surface form Disambiguated ID Type / Status
Subject Ryan White Part F E637335 entity
Predicate relatedTo P37 FINISHED
Object Ryan White Part D
Ryan White Part D is a component of the Ryan White HIV/AIDS Program that funds comprehensive outpatient and family-centered care, including support services, for women, infants, children, and youth living with HIV.
E642465 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ryan White Part D | Statement: [Ryan White Part F, relatedTo, Ryan White Part D]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ryan White Part D
Triple: [Ryan White Part F, relatedTo, Ryan White Part D]
Generated description
Ryan White Part D is a component of the Ryan White HIV/AIDS Program that funds comprehensive outpatient and family-centered care, including support services, for women, infants, children, and youth living with HIV.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e75db6c97081908178383fa632b193 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f6dd99f88190848a5bbee795aa17 completed May 2, 2026, 1:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ec8a5c4481909e636b76a3732818 completed May 22, 2026, 11:53 p.m.
NEDg Description generation batch_6a10ed61eafc8190b74041bee59908fd completed May 22, 2026, 11:57 p.m.
NED2 Entity disambiguation (via description) batch_6a10ee124ba48190a53c16f69b303aae completed May 23, 2026, midnight
Created at: April 21, 2026, 1:59 p.m.